STOCK PORTFOLIO OPTIMIZATION IN BULLISH AND BEARISH CONDITIONS USING THE BLACK-LITTERMAN MODEL
:
https://doi.org/10.9744/jmk.25.2.92-104Keywords:
Bullish and bearish, optimal portfolio, Black-Litterman modelAbstract
Bullish and bearish phenomena characterize the development of the capital market. Therefore, this study aimed to identify and analyze bullish and bearish conditions in the Indonesian capital market to formulate an optimal portfolio. The sample consisted of 20 selected companies based on their substantial market capitali- zation. The results showed that from January 2011 to December 2020, the capital market experienced 77 bullish and 43 bearish months. The transition probability from bullish to bearish and bearish to bullish state was 15.67% and 56.14%. Furthermore, employing the Markov-switching model for determining market conditions and using the Black-Litterman model for portfolio construction proved advantageous for investors' financial forecasting techniques and their potential to generate valuable insights to create a well-informed portfolio.
References
Andrei, M. S., & Hsu, J. S. J. (2020). A Bayesian approach for asset allocation. International Journal of Statistics and Pro-bability, 9(4), 1–14. https://doi.org/10.5539/ijsp.v9n4p1
Arisena, A., Noviyanti, L., & Soleh, A. Z. (2018). Portfolio return using Black-Litterman single view model with ARMA-GARCH and Treynor Black model. Journal of Physics: Conference Series, 974(1), 1–6. https://doi.org/10.1088/1742-6596/974/1/012023
Bai, J., & Perron, P. (2003). Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18(1), 1–22. https://doi. org/10.1002/jae.659
Barua, R., & Sharma, A. K. (2022). Dynamic Black Litterman portfolios with views derived via CNN-BiLSTM predictions. Finance Research Letters, 49, 103111. https://doi.org/10.1016/j.frl.2022.103111
Bessler, W., Opfer, H., & Wolff, D. (2014). Multi-asset portfolio optimization and out-of-sample performance: An evaluation of Black–Litterman, meanvariance, and naïve diversification approaches. European Journal of Finance, 23(1), 1–30. https://doi.org/10.1080/1351847X.2 014.953699
Brigham, E. F., & Houston, J. F. (2009). Fundamentals of financial management, 12th Edition. South-Western College Pub.
Chen, S. D., & Lim, A. E. B. (2020). A ge¬neralized Black-Litterman model. Operations Research, 68(2), 381–410. https://doi.org/10.1287/opre.2019.18 93
De la Torre-Torres, O. V., Galeana-Figueroa, E., Del Río-Rama, M. de la C., & Álvarez-García, J. (2022). Using Markovswitching models in US stocks optimal portfolio selection in a Black–Litterman context (Part 1). Mathematics, 10(8), 1296. https://doi.org/10.3390/math1008 1296
Dinahastuti, D., Badruzaman, J., & Wursan, E. R. (2019). Effect of capital asset pricing model on stock prices. Asian Journal of Economics, Business, and Accounting, 13(3), 1–11. https://doi.org/10.9734/ajeba/2019/v13i330172
Fabozzi, F. J., & Francis, J. C. (1979). Mutual fund systematic risk for bull and bear markets: An empirical examination. The Journal of Finance, 34(5), 1243–1250. https://doi.org/10.1111/j.1540-6261.1979.tb00069.x
Fuhrer, A., & Hock, T. (2023). Uncertainty in the Black–Litterman model: empirical estimation of the equilibrium. Journal of Empirical Finance, 72, 251–275. https://doi.org/10.1016/j.jempfin.2023.03.009
Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica, 57(2), 357–384. https://doi.org/10.2307/1912559
Huuhka, T. (2022). Regime-based Black-Litterman model for the strategic asset allocation of insti-tutional investors. Thesis. School of Science, Aalto University.
Ivanova, M., & Dospatliev, L. (2017). Application of Markowitz portfolio optimization on Bulgarian stock market from 2013 to 2016. International Journal of Pure and Applied Mathematics, 117(2), 291–307. https://doi.org/10.12732/ijpam.v117i2.5
Izzati, L., Sulistianingsih, E., & Wira, R. S. (2019). Analisis pengukuran kinerja portofolio optimal indeks saham LQ45 dengan model Black-litterman. Bimaster: Buletin Ilmiah Matematika, Statistika dan Terapannya, 8(3), 555–562. https://doi.org/10.26418/bbimst.v8i3.33904
Kara, M., Ulucan, A., & Atici, K. B. (2019). A hybrid approach for generating investor views in Black–Litterman model. Expert Systems with Applications, 128, 256–270. https://doi.org/10.1016/j.eswa.2019.03.041
Kolm, P. N., Ritter, G., & Simonian, J. (2021). Black-litterman and beyond: The Bayesian paradigm in investment management. Journal of Portfolio Management, 47(5), 91–113. https://doi.org/10.3905/JPM.2021.1.222
Mahmuda, H. S., & Subekti, R. (2017). Analisis penilaian kinerja Black- Litterman menggunakan information ratio dengan benchmark capital aset pricing model. Jurnal Kajian dan Terapan Matematika, 6(4), 52–58.
Mahrivandi, R., Noviyanti, L., & Setyanto, G. R. (2017). Black-Litterman model on non-normal stock return (Case study four banks at LQ-45 stock index). AIP Conference Proceedings, 1827(March), 1–7. https://doi.org/10.1063/1.4979429
Makridakis, S., Wheelwright, S.C., & McGee, V. E. (1993). Metode dan aplikasi peramalan, alih bahasa Andriyanto, U. S. & Basith, A. Jakarta: Erlangga.
Martin, K. J., & Sankaran, H. (2019). Using the Black-litterman model: A view on opinions. Journal of Investing, 28(1), 112–122. https://doi.org/10. 3905/joi.2019.1.075
Maulana, Y. (2020). Stock investment portfolio analysis with single index model. Indonesian Journal of Business and Economics, 3(2), 529–536. https://doi.org/ 10.25134/ijbe.v3i2.3717
Meucci, A. (2006). Beyond Black-Litterman in practice: A five-step recipe to input views on non-normal markets. SSRN Electronic Journal, 1–15. https://doi.org/10.2139/ssrn.872577
Megginson, W. L. (1997). Corporate finance theory. New York: Addison-Wesley.
Min, L., Dong, J., Liu, D., & Kong, X. (2021). A Black-litterman portfolio selection model with investor opinions generating from machine learning algorithms. Engineering Letters, 29(2), EL _29_2_40.
Mourtas, S. D., & Katsikis, V. N. (2022). Ex¬plo¬iting the Black-Litterman framework through error-correction neural networks. Neurocomputing, 498, 43–58. https://doi.org/10.1016/j.neucom.2022.05.036
Murtadina, U. A., Saputro, D. R. S., & Uto¬mo, P. H. (2021). The application of Black-Litterman Bayesian model for the portfolio optimization on the liquid index 45 (LQ45) with information ratio assessment. AIP Conference Proceedings, 2326, 1–8. https://doi.org/10.1063/5.0039684
Olsson, S., & Trollsten, V. (2018). The Black Litterman asset allocation model an empirical comparison of approaches for implications for risk-return characteris¬tics. Master Thesis. Linköping University.
Oprisor, R., & Kwon, R. (2020). Multi-period portfolio optimization with investor views under regime switching. Journal of Risk and Financial Management, 14(1), 3. https://doi.org/10.3390/jrfm14010003
Pudjiani, M., Syaukat, Y., & Irawan, T. (2020). Optimum portfolio analysis of the Black-litterman model in the Indonesian stock exchange on consumer goods industrial sector. The Winners, 21(1), 27–33. https://doi.org/10.21512/tw.v21i1.5954
Ratri, A. V. D. K. (2015). Analisis portofolio optimum saham syariah dengan model Black-Litterman. Jurnal Fourier, 4(1), 1–21. https://doi.org/10.14421/fourier.2 015.41.31-42
Shahid, A. (2019). Portfolio optimization using Black Litterman model: Case of Pakistan stock exchange. Thesis. Institute of Management Science, Bahauddin Zakariya University Multan.
Sholehah, N. A., Permadhy, Y. T., & Yetty, F. (2020). The comparison of optimal portfolio formation analysis with single index and capital asset pricing models in making investment decisions. European Journal of Business and Management Research, 5(4), 1–9. https://doi.org/10.24018/ejbmr.2020.5.4.470
Stoilov, T., Stoilova, K., & Vladimirov, M. (2022). Decision support for portfolio management by information system with Black-litterman model. International Journal of Information Technology and Decision Making, 21(2), 643–664. https://doi.org/10.1142/S0219622021500589
Su, S. S. W., Kek, S. L., & Abdullah, M. A. A. (2019). Using historical return data in the Black-litterman model for optimal portfolio decision. Journal of Science and Technology, 11(2), 17–25.
Subekti, R. (2009). Keunikan model Black- Litterman dalam pembentukan portofolio. Prosiding Semi-nar Nasional Penelitian, Pendidikan dan Penerapan MIPA, 147–150.
Subekti, R., Abdurakhman, A., & Rosadi, D. (2022). The efficiency frontier of Markowitz and Black-Litterman. Proceedings of the 4th International Seminar on Innovation in Mathematics and Mathe¬matics Education (ISIMMED) 2020, AIP Procedings, 2575(1), 070005.
Ta, B. Q., & Vuong, T. (2020). The Black-Litterman model for portfolio optimization on the Vietnam stock market. International Journal of Uncertainty, Fuzziness, and Knowlege-Based Systems, 28 (Supp01), 99–111. https://doi.org/10.1142/S0218488520400097
Tambunan, D. (2020). Investasi saham di ma-sa pandemi covid-19. Widya Cipta: Jur¬nal Sekretari dan Manajemen, 4(2), 117 –123. https://doi.org/10.31294/widyacip ta.v4i2.8564
Tandelilin, E. (2001). Beta pada pasar bullish dan bearish: Studi empiris di Bursa Efek Jakarta. Jurnal Ekonomi dan Bisnis Indonesia, 16(3), 261–272.
Tandelilin, E. (2017). Pasar modal: Manajemen portofolio dan investasi. Yogyakarta: PT Kanisius.
Wutsqa, D. U., Pamungkas, M. A., & Subek¬ti, R. (2021). Black-litterman model with views prediction using Elman recurrent neural network. Universal Journal of Accounting and Finance, 9(6), 1297–1311. https://doi.org/10.13189/ujaf.2021.090609
Downloads
Published
How to Cite
Issue
Section
License
Authors who publish on this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).